1. Field of the Invention
The present invention relates to a security technology and a technology for constituting an auxiliary system of a distributed computer resource management technology in a microprocessor level that are important in using grid computing.
2. Description of the Related Art
A grid computing technique is often taken up as a key word of IT (Information Technology). “Grid” is a word that is derived from “power grid” (a high-voltage line transmission network), and comes from an idea of utilizing the computing performance by combining the computers which are distributed geographically without minding a generation location, like electricity. The word “grid” has emerged in 1998 by Ian Foster of Argonne National Laboratory in U.S.A. (Reference 1. Ian Foster, “The Grid: Blueprint for a New Computing Infrastructure”, Morgan-Kaufmann, July 1998 Internet <URL:http://www.bh.com//mk/default.asp?isbn=1558604758>). Note that the content of grid computing is made considering the flow of distributed computing or cluster computing that has been developed so far.
A mechanism for constituting grid computing is now conducted mainly in a middleware level, and Globus ToolKit is a certain de facto standard. Globus ToolKit is developed by the Globus project team where Argonne National Laboratory in U.S.A., universities in U.S.A. such as University of Southern California and companies such as IBM and Microsoft participate in. Globus ToolKit has a primitive function required for grid computing, that is to say, provides only functions of resource management, resource information service and data management that are directly connected to a platform such as an operating system (OS).
Therefore, it is not easy to operate grid computing by only using Globus ToolKit, but more and more middlewares collaborating with Globus ToolKit aiming at grid computing operation appear. There are various methods for utilizing grid computing. Herein, metacomputing, high throughput computing, mega computing, grid portal, data grid, and access grid are introduced briefly as typical methods for utilization, for making a technical background clear.
First, metacomputing is a method for solving a large scale problem that cannot be treated with only one computer, by using plural computers that are connected to one another in a grid environment. A parallel processing among plural computers using MPI (Message Passing Interface) is an implementation method of metacomputing. A large number of middlewares that realize MPI among plural computers each employ an MPI supplied by a vendor in a computer and establish communication between computers by TCP/IP. It is possible to put a parallel program developed in MPI in action in a grid environment without giving a large change, by using these middlewares.
High throughput computing is a method for distributing a large number of processing into computer resources in grid and executing them at high speed. As a specific achievement method, there are a method that a large number of jobs are scheduled and injected into plural resources, and a method that a remote computer that is referred to as RPC (Remote Procedure Call) is asked to perform a process. There is a function to make a job for a local resource in Globus Toolkit, but information of a job must be specified in an API, which is complicated and which is referred to as RSL (Resource Specification Language). In addition, it has a function (DUROC: Dynamically Updated Request Online Co-allocator) to secure plural resources simultaneously, but does not have a scheduling function to perform a load distribution of a job between resources. It is a simple and easy implementation method of high throughput computing that a job manager for a local resource and a scheduler for performing a dynamic load distribution between resources are combined with Globus.
Mega computing is a method by which computers such as personal computers in idling in the world are utilized efficiently, and various data are analyzed, and the number of the computers to be used is assumed to be several million or more literally. As a typical example of use, there is a search project of evidence of intelligent extraterrestrial life “SETI@home (Search for Extra-Terrestrial Intelligence)”. A system of this project has been studied by David Anderson in University of California since 1997, an experiment by entry of general personal computers is started in May, 1999, and the project is so big that the number of the personal computers is four million or more.
Grid portal is a method that utilizes a single-sign-on to enable an access to plural sites with one log-in and that can make various resources in a grid or use of service simple and easy.
There is a portal providing an access means to a computing resource itself or a portal providing an access to a function. Portals can improve further convenience by adding functions such as scheduling, a search or comparison of past computed results, a service cooperation of plural sites, rather than a simple service inlet. The technology development about portals is pushed forward also in the world of Web service, and various specifications such as WSIA (Web Services for Interaction Applications), WSRP (Web Services for Remote Portals), and WSXL (Web Services eXperience Language) coexist.
A grid focusing on enormous data as an information resource is referred to as a data grid. In an field such as high energy physics, astrophysics, or bioinformatics, there are more and more needs for sharing of measured data, and the data grid is useful since cooperation of a large number of researchers for analysis is necessary, in the case where the number of observation devices is small but obtained data are enormous, or in the case where data becomes enormous because there is a great deal of measuring objects although the number of devices is large. There is a need to handle data as a distributed file because data size is large and cannot be treated in one place in a science and technology field. In addition, research and development about handling of database in a grid has been performed.
Access grid is a project and software that Argonne National Laboratory in U.S.A. is leading, aims at a human interaction support in a grid, and is a method that can perform a high collaboration by sharing an image of hearing or visual senses with a researcher in a remote location. A sense of reality is more favorable as compared with a conventional video teleconference system and it is greatly different from a commodity personal computer in using software. Accordingly, the number of screens, cameras, or microphones can be increased easily and an access grid node having an arbitrary scale can be built. In addition, high scalability is realized by employing an IP multicast and a broadband backbone, and collaboration at several tens or more of spots is possible.
Grid computing has various diversities and a future with a rapid spread of a network technique as described above. In addition, it has also large expectations for business. However, there are some problems which must be settled in order to promote the spread of grid computing. Especially important problems are the two problems described below.
The first problem is security. In grid computing, security is extremely difficult and thorny. When employed computer resources are very expensive, in many cases, the computer resources belong to different management areas. In addition, there is a case where an executed application includes a confidential matter of a company or a case where it is treated as a valuable asset. Therefore, it is necessary for a user to have “a key” for each of computer resources and data, in addition to a certain mechanism of authentication and authorization. However, when several hundreds or millions of computer resources that are distributed are utilized for solving one complex problem, it is conceivable that a procedure for use is to be single. A standard of existing software security like SSL and X.509 is being improved to satisfy these requests. Further, security infrastructure in grid computing is already included in the existing grid computing environment like Globus.
The second problem relates to resource management technology. A difficult problem in a grid computing environment is a management of distributed computer resources (DRM: distributed resource management), and relates to monitoring states of computer resources and data resources connected by network, scheduling of a job and a resource, an execution method thereof and the like. Specifically, when a large number of sleeping resources are used as typified by mega computing, it is necessary to adequately consider an object that is to reduce the power consumption.